pytorch将cpu训练好的模型参数load到gpu上,或者gpu->cpu上
假设我们只保存了模型的参数(model.state_dict())到文件名为modelparameters.pth, model = Net()
1. cpu -> cpu或者gpu -> gpu:
checkpoint = torch.load('modelparameters.pth')
model.load_state_dict(checkpoint)
2. cpu -> gpu 1
torch.load('modelparameters.pth', map_location=lambda storage, loc: storage.cuda(1))
3. gpu 1 -> gpu 0
torch.load('modelparameters.pth', map_location={'cuda:1':'cuda:0'})
4. gpu -> cpu
torch.load('modelparameters.pth', map_location=lambda storage, loc: storage)
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